Cloud resolving models are considered one of the best tools that can simulate cloud systems and their growth over time. Within cloud systems, there are many different parameters involving moisture and ice that can have major effects on the overall system. Thus the ice crystal fall speed, is analyzed to see how it affects the cloud system. We hypothesize that cloud systems will increase in size and grow deeper when ice crystal fall speeds are slower, and inversely that cloud systems will decrease in size and become more shallow when ice crystal fall speeds are faster. Observed large-scale forcing was obtained using data from the DYNAMO (Dynamics of the Madden-Julien Oscillation) experiment over the Indian Ocean. A Clark-Hall cloud resolving model was then run with the forcing to compare the model simulation against observations. Two different cloud simulations were run with faster and slower ice fall speeds to compare to the original control test. Shortwave and longwave radiation and mixing ratio plots were used to analyze the size of the clouds in relation to ice crystal fall speeds. Results show that the cloud model was also able to simulate cloud systems and their characteristics without much bias. They also show that cloud systems are larger with slower ice fall speeds and smaller with faster ice fall speeds.